Information processing device and information processing method

Abstract

An information processing device (10) comprises: a reception unit (11) that receives generation request information for a stimulus of a virtual object which is realized in a virtual space; an acquisition unit (12) that, in response to the reception of the generation request information for the stimulus of the virtual object, acquires information for generating the stimulus of the virtual object and image data pertaining to the appearance of the virtual object; and an output unit (13) that outputs an input sentence to a prompt for instructing the generation the stimulus of the virtual object on the basis of the information for generating the stimulus and the image data pertaining to the appearance.

Description

Information processing device and information processing method

[0001] The present disclosure relates to an information processing device and an information processing method.

[0002] Conventionally, the generation of stimuli (vibrations) has been focused on reproducing things that exist in the real world. For example, a technique for simulating tactile sensations based on stimulus (tactile) parameters has been proposed (see Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2023-148855

[0004] However, the tactile sensation of objects that do not exist in the real world is still in the research stage, and little is known about it. However, as virtual spaces such as the Metaverse have become popular in recent years, it is fully expected that there will be an increasing need to touch various objects realized in virtual spaces (hereinafter referred to as "virtual objects") and experience their tactile sensations. The same is true for other stimuli such as smell. Therefore, technology that can generate tactile stimuli for virtual objects is highly anticipated.

[0005] Meanwhile, in recent years, various types of content have been generated using generative artificial intelligence (AI) models. A generative AI model is a model that can generate content (generation results) in response to a prompt containing input information, according to any one or a combination of instructions, context, questions, and output formats indicated by the prompt, and return the generated content as response information.

[0006] Therefore, the present disclosure aims to utilize a generative AI model to obtain information for generating tactile and other stimuli of virtual objects.

[0007] The information processing device according to the present disclosure includes a reception unit that receives request information for generating a stimulus for a virtual object realized in a virtual space, an acquisition unit that acquires information for generating a stimulus for the virtual object and image data related to the appearance of the virtual object in response to the reception of the request information for generating a stimulus for the virtual object, and an output unit that outputs an input sentence to a prompt for instructing the generation of a stimulus for the virtual object based on the information for generating the stimulus and the image data related to the appearance.

[0008] According to the present disclosure, a generative AI model can be utilized to obtain information for generating tactile and other stimuli of a virtual object.

[0009] FIG. 1 is a configuration diagram of an entire system including an information processing device; FIG. 2 is a flow diagram of processing executed by the information processing device; FIG. 3 is a diagram showing an example of an image relating to the appearance of a virtual object and information for generating stimuli for the virtual object; FIG. 4 is a diagram showing an example of an input sentence to a prompt; FIG. 5 is a diagram showing another system configuration example; and FIG. 6 is a diagram showing a hardware configuration example of an information processing device.

[0010] Hereinafter, an embodiment of an information processing device and an information processing method according to the present disclosure will be described with reference to the drawings. In the following embodiment, a form will be described in which a large language model (LLM) that is mainly used for text generation is used as an example of a generative AI model.

[0011] 1 shows a configuration diagram of a system 1 including an information processing device 10 according to the present disclosure. As shown in Fig. 1, the system 1 includes an external server 30A on which a large-scale language model (LLM) 30 runs, the information processing device 10, and an in-house server 20A on which an in-house system runs. The in-house server 20A includes an in-house database (in-house DB) 20 that stores in advance various data to be processed in the in-house system (such as information for generating stimuli for virtual objects described below and image data related to the appearances of virtual objects), and a learning model 21 that has undergone machine learning to learn combinations of various appearance images and stimuli of virtual objects described below.

[0012] In this specification, the term "virtual object" refers to various objects realized in a virtual space, but broadly includes objects that do not exist in the real world but are created in the virtual space, and objects that imitate objects existing in the real world and are reproduced in the virtual space. "Stimulus" refers to information related to various sensations experienced by the user from a virtual object (tactile sensation (vibration, hardness), smell, sound, etc.), which is output to the information processing device 10 operated by the user. "Stimulus-related parameters" may be, for example, information indicating the type of stimulus or information indicating its level. For example, information indicating the type of stimulus may be sound, vibration, etc., and information indicating its level may be volume (information indicating volume such as 0 to 50) or information indicating the type and magnitude of vibration. "Virtual object stimulation" refers to various sensations experienced by the user from the virtual object (tactile sensation, smell, etc.). In this embodiment, a device that generates (reproduces) the stimulation of a virtual object is already available, and information (i.e., stimulation-related parameters) for such a device to generate (reproduce) the stimulation is generated by the LLM 30. The above-mentioned device may be an external device connectable to the information processing device 10, or may be an application that realizes a generation (reproduction) function by being installed in the information processing device 10. Note that the information processing device 10 may employ various information processing devices (smartphones, mobile phones, smartwatches, wearable devices, laptops, desktop computers, servers, etc.) as hardware.

[0013] An RAG (Retrieval-Augmented Generation) system application is installed on the information processing device 10, and the RAG system operates. The RAG system is a type of prompt extension technology used for corporate information sharing between LLMs. Specifically, when a generation request is made to an LLM using an instruction (input text in response to a prompt) based on a content generation request, the system searches for related information (reference information) in advance if necessary and requests the LLM to generate the content together with the instruction. The present disclosure corresponds to an invention that extends and improves the functionality of the RAG system. It has an aspect of enriching and optimizing the instruction (input text in response to a prompt) for the LLM 30 using information acquired from an internal database 20 that cannot be directly accessed by the LLM 30 and a learning model 21. To realize the functions related to the present disclosure, the information processing device 10 includes a receiving unit 11, an acquisition unit 12, and an output unit 13. The functions of each unit are described below.

[0014] The reception unit 11 is a functional unit that receives request information for generating a stimulus for a virtual object to be realized in a virtual space. The request information for generating a stimulus for a virtual object is request information that is notified to the reception unit 11 when a generation request button provided on a web page or an application page displayed on the display of the information processing device 10 is pressed.

[0015] The acquisition unit 12 is a functional unit that acquires information for generating stimuli for a virtual object and image data related to the appearance of the virtual object by searching an external database (here, the internal database 20) or from the generation request information entered by the user in response to receiving a request for generating stimuli for a virtual object. The "image data" may be a blueprint, design drawing, or image of the virtual object itself, or may be an image representing a characteristic part of the virtual object or an image for expressing a stimulus emitted from the virtual object. The "information for generating stimuli for a virtual object" includes at least one of the following: information related to the role, task, and conditions of the virtual object; information related to the appearance (shape, pattern, color, size, etc.); and information related to display in the virtual space (display location, display timing, etc.). The acquisition unit 12 also has a function of searching the internal database 20 using keywords corresponding to the request for generating stimuli for a virtual object. For example, the acquisition unit 12 acquires information for generating stimuli for a virtual object, such as a dragon, by searching the internal database 20 using the keyword "dragon" shown in FIG. 3 .

[0016] The output unit 13 is a functional unit that outputs an input sentence (an instruction sentence for the LLM 30) to a prompt that instructs the generation of a virtual object stimulus based on the acquired information for stimulus generation and image data related to the appearance of the virtual object. In addition, the output unit 13 receives and outputs information for generating a virtual object stimulus as a generation result output from the LLM 30 in response to the input sentence to the prompt. The "information for generating a virtual object stimulus" here includes parameters related to stimuli such as the touch and temperature of the dragon, which is a virtual object (for example, the touch of a hot temperature, or the touch of a rough surface with hard scales).

[0017] Furthermore, the output unit 13 includes information indicating the "degree" of the conditions for generating tactile stimuli for the virtual object in the input sentence for the prompt. For example, regarding "hardness," one of the conditions for generating tactile stimuli for a dragon virtual object, by including information indicating the degree such as "The center of each scale is 'very hard.' The scales gradually become softer toward the periphery, which is 'slightly soft.'" in the input sentence, it is possible to instruct the generation of complex tactile stimuli that seem to have been thought up by a human. Note that the information indicating the degree may be information received from the user or may be determined based on information registered in advance by the operator.

[0018] In this embodiment, the output unit 13 uses a learning model 21 that has undergone machine learning to learn combinations of various virtual object appearance images and stimuli. Specifically, the output unit 13 inputs image data related to the appearance of the virtual object into the learning model 21, acquires "at least one piece of stimulus information that matches the image data" output from the learning model 21, and includes the acquired stimulus information in the input sentence for the prompt. This is expected to enable the LLM 30 to obtain parameters for generating stimuli that better match the appearance of the virtual object.

[0019] [Regarding Processing Executed in Information Processing Apparatus] Hereinafter, processing executed in the information processing apparatus 10 (processing related to the information processing method of the present disclosure) will be described with reference to the flow diagram of FIG.

[0020] When a user presses a generation request button provided on a web page or application page displayed on the display of the information processing device 10, information requesting the generation of a virtual object stimulus is notified to the reception unit 11, and the reception unit 11's acceptance of the generation request information triggers the start of the processing of Figure 2.

[0021] In response to receiving the generation request information, the acquisition unit 12 acquires the information for generating the virtual object and image data related to the appearance of the virtual object by searching an external database (here, the in-house DB 20) or from the generation request information (step S1). For example, the acquisition unit 12 acquires image data related to the appearance of the virtual object and information for generating the virtual object, as shown in FIG. 3, from the generation request information, and further acquires detailed specification information related to the dragon by searching the in-house DB 20. As a result, the following information for generating the virtual object is acquired: "Dragon; Red body surface; Scales on body surface; Body length: 15 m; Fire-breathing..."

[0022] Next, the output unit 13 outputs an input sentence for a prompt instructing the generation of a virtual object based on the information for generating the virtual object and image data related to its appearance (step S2). As described above, the output unit 13 inputs image data related to the appearance of the virtual object into the learning model 21, thereby acquiring "at least one piece of stimulus information matching the image data" output from the learning model 21, and includes the acquired stimulus information in the input sentence for the prompt. The input sentence for the prompt may include, for example, information related to the role, task, and condition, as well as information related to the shape, pattern, color (e.g., red, blue, white, etc.), size, display location in the virtual space, and display timing. Among the above, "size" may include, for example, information representing the width, depth, and height, size along the X, Y, and Z axes in a three-dimensional coordinate system in the virtual space, and size relative to existing structures. For example, an input sentence including multiple items such as role, task, and condition, as shown in FIG. 4, may be: "Role: You are the creator of a virtual object. Task: Generate parameters for generating tactile stimuli for the virtual object." Conditions: The virtual object is a dragon. It has numerous scales on its surface. - The center of each scale is "very hard." - It gradually becomes softer towards the edge of each scale, which is "slightly soft." - The surface of the body is hot. - Avoid anything that is uncomfortable. ..." By including information indicating the degree of "hardness," as in the example above, it is possible to generate parameters that generate complex tactile stimuli that are as if they were thought up by a human.

[0023] Thereafter, information regarding the stimulus of the virtual object (i.e., parameter information for reproducing the stimulus) is output from the LLM 30 as the generation result, and the output unit 13 acquires and outputs the generation result (the above-mentioned parameter information) from the LLM 30 (step S4).

[0024] In this way, the generation AI model (LLM30) can be utilized to acquire information (stimulus-related parameter information) for generating tactile and other stimuli of a virtual object. This allows the user to input the parameter information into a device (an external device or an installed application on the information processing device 10) that generates the virtual object stimuli, thereby displaying the virtual object in a virtual fantasy and recreating and enjoying the stimuli of the virtual object.

[0025] (Modification of System 1) System 1 is not limited to the configuration shown in FIG. 1 , and may have a configuration in which LLM 30 is implemented in information processing device 10, as shown in FIG. 5 . This configuration can be realized by installing an application that executes the functions of LLM 30 in information processing device 10. Furthermore, although FIGS. 1 and 5 show examples in which map DB 20 and music information DB 21 are implemented outside information processing device 10 (for example, on a network), one or both of these may be implemented inside information processing device 10.

[0026] The gist of the present disclosure lies in the following [1] to [8]. [1] An information processing device comprising: a receiving unit that receives request information for generating a stimulus for a virtual object realized in a virtual space; an acquisition unit that acquires information for generating a stimulus for the virtual object and image data related to the appearance of the virtual object in response to the reception of the request information for generating a stimulus for the virtual object; and an output unit that outputs an input sentence for a prompt for instructing generation of the stimulus for the virtual object based on the information for generating the stimulus and the image data related to the appearance. [2] The information processing device described in [1], wherein the acquisition unit acquires the information for generating the stimulus and the image data related to the appearance by searching an external server or from the generation request information. [3] The information processing device described in [1] or [2], wherein the output unit includes information indicating a degree of a condition related to generation of a stimulus for the virtual object in the input sentence for the prompt. [4] The information processing device described in any one of [1] to [3], wherein the output unit acquires at least one piece of stimulus information that matches the image data using a learning model that has been machine-learned on combinations of appearance images and stimuli of various virtual objects, and includes the acquired stimulus information in the input sentence for the prompt. [5] The information processing device according to any one of [1] to [4], wherein the output unit receives and outputs parameters for reproducing a stimulus for the virtual object as a generation result output from a generative AI model in response to input of the input sentence to the prompt. [6] An information processing method comprising: a step by the information processing device receiving generation request information for a stimulus for a virtual object realized in a virtual space, a step by the information processing device acquiring information for generating a stimulus for the virtual object and image data related to an appearance of the virtual object in response to the reception of the generation request information for the stimulus for the virtual object, and a step by the information processing device outputting an input sentence to a prompt for instructing generation of a stimulus for the virtual object based on the information for generating the stimulus and the image data related to the appearance.

[0027] [Explanation of Terms, Explanation of Hardware Configuration (FIG. 6), etc.] The block diagrams used in the description of the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (e.g., wired, wireless, etc.) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

[0028] Functions include, but are not limited to, judgment, determination, assessment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0029] For example, an information processing device according to an embodiment of the present disclosure may function as a computer that executes the processes of the present disclosure. Fig. 6 is a diagram illustrating an example of a hardware configuration of an information processing device 10 according to an embodiment of the present disclosure. The information processing device 10 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0030] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the information processing device 10 may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0031] Each function of the information processing device 10 is realized by loading specified software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communication via the communication device 1004, and control at least one of reading and writing data in the memory 1002 and storage 1003.

[0032] The processor 1001 controls the entire computer by running, for example, an operating system, and may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc.

[0033] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. While the various processes have been described as being executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may be transmitted from a network via a telecommunications line.

[0034] The memory 1002 is a computer-readable recording medium and may be configured by, for example, at least one of a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to an embodiment of the present disclosure.

[0035] Storage 1003 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including at least one of memory 1002 and storage 1003.

[0036] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD).

[0037] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

[0038] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0039] The information processing device 10 may also be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0040] The notification of information is not limited to the aspects / embodiments described in the present disclosure and may be performed using other methods. For example, the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI) and Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB) and System Information Block (SIB))), other signals, or a combination thereof. Furthermore, the RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, or the like.

[0041] Each aspect / embodiment described in the present disclosure may be implemented using any of the following standards: LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (xG (x is, for example, an integer or a decimal number)), FRA (Future Radio Access), NR (new Radio), New radio access (NX), Future generation radio access (FX), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.17 (WiMAX (registered trademark)), IEEE 802.19 (WiMAX (registered trademark)), IEEE 802.20 (WiMAX (registered trademark)), IEEE 802.21 (Wi-Fi (registered trademark)), IEEE 802.22 (WiMAX (registered trademark)), IEEE 802.23 (WiMAX (registered trademark)), IEEE 802.24 (WiMAX (registered trademark)), IEEE 802.25 (WiMAX (registered trademark)), IEEE 802.26 (WiMAX (registered trademark)), IEEE 802.27 (WiMAX (registered trademark)), IEEE 802.28 (WiMAX (registered trademark)), IEEE 802.29 (WiMAX (registered trademark)), IEEE 802.30 (WiMAX (registered trademark)), IEEE 802.31 (Wi-Fi (registered trademark)), IEEE 802.32 (WiMAX (registered trademark)), IEEE 802.33 (WiMAX (registered trademark)), IEEE 802.34 ( The present invention may be applied to at least one of systems using 802.20, Ultra-Wideband (UWB), Bluetooth, or other suitable systems, and next-generation systems that are extended, modified, created, or defined based on these systems. It may also be applied to a combination of multiple systems (e.g., a combination of LTE and / or LTE-A with 5G).

[0042] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0043] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be transmitted to another device.

[0044] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0045] The aspects / embodiments described in this disclosure may be used alone, in combination, or switched depending on the implementation. Notification of predetermined information (e.g., notification that "X is true") is not limited to explicit notification, but may be implicit (e.g., not notifying the predetermined information).

[0046] Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0047] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0048] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0049] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0050] Note that terms described in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Furthermore, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

[0051] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0052] Furthermore, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information. For example, a radio resource may be indicated by an index.

[0053] The names used for the above-described parameters are not intended to be limiting in any way. Furthermore, the mathematical expressions using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (e.g., PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not intended to be limiting in any way.

[0054] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0055] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0056] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0057] When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0058] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0059] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0060] 1...system, 10...information processing device, 11...reception unit, 12...acquisition unit, 13...output unit, 20...in-house DB, 21...learning model, 20A...in-house server, 30...LLM, 30A...external server, 1001...processor, 1002...memory, 1003...storage, 1004...communication device, 1005...input device, 1006...output device, 1007...bus.

Claims

1. An information processing device comprising: a reception unit that receives request information for generating a stimulus for a virtual object realized in a virtual space; an acquisition unit that acquires information for generating a stimulus for the virtual object and image data related to the appearance of the virtual object in response to the reception of the request information for generating a stimulus for the virtual object; and an output unit that outputs an input sentence to a prompt for instructing the generation of a stimulus for the virtual object based on the information for generating the stimulus and the image data related to the appearance.

2. The information processing device according to claim 1, wherein the acquisition unit acquires the information for generating the stimulus and the image data relating to the appearance by searching an external server or from the generation request information.

3. The information processing device according to claim 1, wherein the output unit includes information indicating a degree of a condition for generating a stimulus of the virtual object in an input sentence for the prompt.

4. The information processing device according to claim 1, wherein the output unit acquires at least one piece of stimulus information that matches the image data using a learning model that has undergone machine learning of combinations of appearance images and stimuli of various virtual objects, and includes the acquired stimulus information in an input sentence for the prompt.

5. The information processing device according to claim 1, wherein the output unit receives and outputs parameters for reproducing stimuli of the virtual object as a generation result output from the generative AI model in response to input of the input sentence to the prompt.

6. An information processing method comprising: a step in which an information processing device receives request information for generating a stimulus for a virtual object realized in a virtual space; a step in which the information processing device acquires information for generating a stimulus for the virtual object and image data related to the appearance of the virtual object in response to the reception of the request information for generating a stimulus for the virtual object; and a step in which the information processing device outputs an input sentence to a prompt for instructing the generation of a stimulus for the virtual object based on the information for generating the stimulus and the image data related to the appearance.

Images